{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "42f76e43",
   "metadata": {},
   "source": [
    "# Anyscale\n",
    "\n",
    "Let's load the Anyscale Embedding class."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "6b82f59f",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from langchain_community.embeddings import AnyscaleEmbeddings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "26895c60",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "embeddings = AnyscaleEmbeddings(\n",
    "    anyscale_api_key=\"ANYSCALE_API_KEY\", model=\"thenlper/gte-large\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "eea52814",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "text = \"This is a test document.\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "fbe167bf",
   "metadata": {
    "scrolled": true,
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    }
   ],
   "source": [
    "query_result = embeddings.embed_query(text)\n",
    "print(query_result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "38ad3b20",
   "metadata": {
    "scrolled": true,
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    }
   ],
   "source": [
    "doc_result = embeddings.embed_documents([text])\n",
    "print(doc_result)"
   ]
  }
 ],
 "metadata": {
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   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
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   "nbconvert_exporter": "python",
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 },
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